Answered: Use the linear regression model…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Researchers studying the association between (x)the number of daily hours of intense artificial lightand (y) the rate of plant growth (cm/month) foundsx = 1.5, sy = 3.0, and r = 0.80. The regression modelthey created predicts growth of 5 cm/month with 2 hoursof this light per day. What’s the predicted growth rate for3 hours of artificial light daily?A) 5.4 cm/moB) 5.8 cm/moC) 6.6 cm/moD) 7.0 cm/moE) 7.8 cm/mo
write the regression equation that will predict the number of manatees killed given thenumber of powerboat registrations (in 1000's). Show all work usingformulas for slope, b1, and y-intercept, b0, calculations roundingto 4-decimal places, if necessary. Show all the calculations and math of slope, b1, and y-intercept, b0, calculations roundingto 4-decimal places, if necessary. SHOW ALL WORK! DO NOT USE EXCEL! I need to be able to see every single part and how you got it. attached is the question
What is the equation of a simple linear regression model with one independent variable x and one dependent variable y, given the slope (b1) is 0.5 and y-intercept (b0) is 2?
What is the equation for a simple linear regression model with one independent variable (x) and one dependent variable (y)?
also compute the regression equation in which you predict Y using X as the predictor variable
(d)Assess the regression model's fit
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 50.7 + 0.3x, + 5.2x2, where x, is the tree's height (in feet) and x2 is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. X1 = 70, x, = 8.9 The predicted volume is cubic feet. (Round to one decimal place as needed.)
The equation used to predict annual cauliflower yield (in pounds per acre) is y = 24,121 +4.505x₁ -4.772x₂, where x₁ is the number of acres planted and x2 is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x₁ =35,100, x₂ =35,500 (b) x₁ = 36,800, X2=37,100 (c) x₁ = 37,900, x₂ = 38,000 (d) x₁ =41,100, x₂ = 41,200 (a) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (b) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (c) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (d) The predicted yield is pounds per acre (Round to one decimal place as needed.)
X₁ is the The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = -51.2 +0.4x₁ + 4.8x2, where tree's height (in feet) and x₂ is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x₁ = 73, x₂ = 8.8 (b) x₁ = 67, x₂ = 11.5 (c) x₁ = 85, x₂ = 17.6 (d) x₁ = 92, x₂ = 20.8 cubic feet. (a) The predicted volume is (Round to one decimal place as needed.) (b) The predicted volume is cubic feet. (Round to one decimal place as needed.) (c) The predicted volume is cubic feet. (Round to one decimal place as needed.) (d) The predicted volume is cubic feet. (Round to one decimal place as needed.) Next
The y-intercept in a linear regression model is always relevant and of interest to investigators for every model constructed. True False
The equation used to predict annual cauliflower yield (in pounds per acre) is y =24,231 + 4.417x, - 4.677x,, where x, is the number of acres planted and x, is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x, = 36,100, X2 = 36,500 (b) x, = 37,800, X2 = 38,100 (c) X4 = 38,800, X2 = 39,000 (d) x, = 42,100, X2 = 42,200 %3D %3D (a) The predicted yield is pounds per acre. (Round to one decimal place as needed.)
A high school wants to predict her students' score on a midterm exam y, given the number of hours a student spent studying x1 and the student's average homework grade x2. She obtains the multiple regression equation yˆ=−2.662+4.686x1+0.753x2. Predict the midterm exam score of a student with an average homework grade of 90, who spent 5 hours studying, rounding to the nearest integer.

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Use the linear regression model yˆ=−24.8x+564.38 to predict the y-value for x=63.